iSQI CTFL_Syll_4.0 Exam With Confidence Using Practice Dumps

Boundary Value Analysis (BVA)focuses on test cases at the edges of partitions because defects often occur at boundaries. The temperature ranges are:

≤7 (Too cold → W)

[8-21] (Standstill → X)

[22-29] (Ideal → Y)

≥30 (Too hot → Z)

Atwo-point BVAmeans testing both thelower and upper boundary valuesof each partition.

The correct selection{7,8,21,22,29,30}includes:

7 → Boundary of Too Cold (W)

8 → Lower boundary of Standstill (X)

21 → Upper boundary of Standstill (X)

22 → Lower boundary of Ideal (Y)

29 → Upper boundary of Ideal (Y)

30 → Lower boundary of Too Hot (Z)

This ensures maximum boundary coverage.

To determine the correct execution order that minimizes the number of configuration switches and respects the dependencies, we need to consider the following:

Initial Configuration:CONF1.

Dependencies:

TC1 depends on nothing.

TC2 depends on TC4.

TC3 depends on TC4.

TC4 depends on nothing.

TC5 depends on TC1.

Configuration Requirements:

TC1 requires CONF2.

TC2 requires CONF2.

TC3 requires CONF1.

TC4 requires CONF1.

TC5 requires CONF2.

Given the initial configuration is CONF1, start with test cases that can run on CONF1 and respect the dependencies. Then switch to CONF2 only when necessary. The optimal order to minimize configuration switches is:

Start withTC4(no dependencies, CONF1).

Continue withTC3(depends on TC4, CONF1).

Switch to CONF2.

ExecuteTC2(depends on TC4, CONF2).

Continue withTC1(no dependencies, CONF2).

Finally, executeTC5(depends on TC1, CONF2).

Therefore, the correct order is:

TC4(CONF1)

TC3(CONF1)

TC2(CONF2)

TC1(CONF2)

TC5(CONF2)

Thus, the answer isA. TC4, TC3, TC2, TC1, TC5.

Theratio-based estimation methodrelies on historical relationships betweendevelopment and testing effort.

Using the given5:3 ratio:

Thus, the correct answer is270 person-days (D).

(A) and (C) are incorrectas they overestimate the effort.

(B) underestimates the testing effort based on the ratio.

Ratio-based estimationhelps allocate resources effectively based on past project data.